# training schedule for 20e
train_cfg = dict(type="EpochBasedTrainLoop", max_epochs=20, val_interval=1)
val_cfg = dict(type="ValLoop")
test_cfg = dict(type="TestLoop")

# learning rate
param_scheduler = [
    dict(type="LinearLR", start_factor=0.001, by_epoch=False, begin=0, end=500),
    dict(type="MultiStepLR", begin=0, end=20, by_epoch=True, milestones=[16, 19], gamma=0.1),
]

# optimizer
optim_wrapper = dict(type="OptimWrapper", optimizer=dict(type="SGD", lr=0.02, momentum=0.9, weight_decay=0.0001))

# Default setting for scaling LR automatically
#   - `enable` means enable scaling LR automatically
#       or not by default.
#   - `base_batch_size` = (8 GPUs) x (2 samples per GPU).
auto_scale_lr = dict(enable=False, base_batch_size=16)
